Journal articles on the topic 'Local data association'
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Berglund, Svante, and Anders Karlstr�m. "Identifying local spatial association in flow data." Journal of Geographical Systems 1, no. 3 (October 1, 1999): 219–36. http://dx.doi.org/10.1007/s101090050013.
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Boots, Barry. "Developing local measures of spatial association for categorical data." Journal of Geographical Systems 5, no. 2 (August 1, 2003): 139–60. http://dx.doi.org/10.1007/s10109-003-0110-3.
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Tozetto, Alexandre Vinicius Bobato, Rodolfo Silva da Rosa, Felipe Goedert Mendes, Larissa Rafaela Galatti, Edison Roberto de Souza, Carine Collet, Bruno Monteiro de Moura, and Walan Robert da Silva. "Local de nascimento e data de nascimento de medalhistas olímpicos brasileiros." Brazilian Journal of Kinanthropometry and Human Performance 19, no. 3 (August 24, 2017): 364. http://dx.doi.org/10.5007/1980-0037.2017v19n3p364.
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The aim of the present study was to analyze the association between birthplace and relative age with winning Olympic medals in Brazilian athletes. he sample consisted of 186 Olympic medalist athletes born in Brazil. Data analysis was performed through descriptive (incidence and percentage) and inferential statistics (Chi-Square to binary logistic regression). he association between population contingents and Olympic champions presented a signiicant result (p <0.05); however, no signiicant associations were found with relative age. It was concluded that most Olympic medalists were born in places that present better living conditions, with intermediate MHDI, which appears only in cities with more than 100 thousand habitants, and relative age is not an important criterion in winning medals among athletes investigated.
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Padilla, Washington, Jesús García, and José Molina. "Knowledge Extraction and Improved Data Fusion for Sales Prediction in Local Agricultural Markets." Sensors 19, no. 2 (January 12, 2019): 286. http://dx.doi.org/10.3390/s19020286.
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In this paper, a monitoring system of agricultural production is modeled as a Data Fusion System (data from local fairs and meteorological data). The proposal considers the particular information of sales in agricultural markets for knowledge extraction about the associations among them. This association knowledge is employed to improve predictions of sales using a spatial prediction technique, as shown with data collected from local markets of the Andean region of Ecuador. The commercial activity in these markets uses Alternative Marketing Circuits (CIALCO). This market platform establishes a direct relationship between producer and consumer prices and promotes direct commercial interaction among family groups. The problem is presented first as a general fusion problem with a network of spatially distributed heterogeneous data sources, and is then applied to the prediction of products sales based on association rules mined in available sales data. First, transactional data is used as the base to extract the best association rules between products sold in different local markets, knowledge that allows the system to gain a significant improvement in prediction accuracy in the spatial region considered.
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Padilla, Washington R., and Jesús García. "Data Association Methodology to Improve Spatial Predictions in Alternative Marketing Circuits in Ecuador." Computational Intelligence and Neuroscience 2018 (November 5, 2018): 1–15. http://dx.doi.org/10.1155/2018/6587049.
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This work proposes a methodology that reduces the error of future estimations in commercialization based on multivariate spatial prediction techniques (cokriging) considering the products with strong associations. It is based on the Apriori algorithm to find association rules in sales of agricultural products of local markets. Results show the improvement in spatial prediction accuracy after using the best association rules.
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Li, Hua, and Shoudan Liang. "Local Network Topology in Human Protein Interaction Data Predicts Functional Association." PLoS ONE 4, no. 7 (July 29, 2009): e6410. http://dx.doi.org/10.1371/journal.pone.0006410.
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M. Khedr, Ahmed, Zaher AL Aghbari, and Ibrahim Kamel. "Privacy Preserving Decomposable Mining Association Rules on Distributed Data." International Journal of Engineering & Technology 7, no. 3.13 (July 27, 2018): 157. http://dx.doi.org/10.14419/ijet.v7i3.13.16343.
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In distributed computing, data sharing is inevitable, however, moving local databases from one site to another should be avoided because of the computational overhead and privacy consideration. Most of the data mining algorithms are designed assuming that data repository is stored locally. This paper presents a scheme and algorithms for mining association rules in geographically distributed data. The proposed scheme preserves data privacy of the different geographical site by passing secure messages between them. The algorithms minimize the communication cost by exchanging statistical summaries of the local databases. We provide a privacy and security analysis that shows the privacy preserving aspects of the proposed algorithms. Moreover, the paper presents extensive simulation experiments to evaluate the efficiency of the proposed scheme.
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Ding, Z., T. Mailund, and Y. S. Song. "Efficient whole-genome association mapping using local phylogenies for unphased genotype data." Bioinformatics 24, no. 19 (July 30, 2008): 2215–21. http://dx.doi.org/10.1093/bioinformatics/btn406.
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T, Irma. "Organisasi Komputer Vesa(Video Electronics Standards Association) Local Bus." Al-Khwarizmi: Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam 2, no. 1 (August 19, 2018): 85–90. http://dx.doi.org/10.24256/jpmipa.v2i1.104.
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Vesa (Video Electronics Standards Association) Local Bus merupakan jalur yang dibuat untuk menyesuaikan kecepatan mikroprosesor di dalam komputer. Vesa local bus dibuat oleh Video Electronics Standards Association yang banyak digunakan pada personal computers berbasis Intel 80486 CPU,Vesa local bus berdampingan dengan Isa Slot. Dalam artikel ini akan di tunjukkan bagaimana kemampuan transfer data, apakah bisa mencapai kecepatan maksimum 66 Mhz dengan lebar 64 bit. Dari kajian yang dilakukan terlihat bahwa kemampuan transfer data sebanyak 528 Mb/s dari clock speed 66 Mhz dan lebar bit 64 tidak dapat direalisasikan karena hanya dapat bekerja pada clock speed 33 Mhz dan lebar bit 32 hingga transfer data hanya 132 Mb/s.
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Ramkumar, Thirunavukarasu, Rengaramanujam Srinivasan, and Shanmugasundaram Hariharan. "Synthesizing Global Association Rules from Different Data Sources Based on Desired Interestingness Metrics." International Journal of Information Technology & Decision Making 13, no. 03 (May 2014): 473–95. http://dx.doi.org/10.1142/s0219622014500138.
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Since business houses are generally global, the required data for their corporate decisions are spread over multiple branches at different regions. In such circumstances, local pattern analysis-based global pattern discovery has become an efficient strategy for mining their multiple data sources. The traditional support-confidence framework alone is not enough for assessing the interestingness of synthesized global association rules. In this context, numerous interestingness measures have been developed in the past to meet various situations. Depending on the requirement, local branches and the central head may choose desired interestingness metric for evaluating local frequent-itemsets and global association rules, respectively. In this paper, we present a generalized synthesis procedure for synthesizing global association rules, based on any interestingness metric, from the mined local patterns forwarded by multiple data sources. We have also shown that the synthesized metric values are quite close to the targeted mono-mining results. Examples and experimental studies establish the validity of our proposal.
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Brunsdon, Chris. "Exploratory spatial data analysis and local indicators of spatial association with XLISP-STAT." Journal of the Royal Statistical Society: Series D (The Statistician) 47, no. 3 (September 1998): 471–84. http://dx.doi.org/10.1111/1467-9884.00148.
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Finke, Roger, and Amy Adamczyk. "The Association of Religion Data Archives (ARDA): Online Research Data, Tools and References." Politics and Religion 1, no. 3 (October 27, 2008): 456–70. http://dx.doi.org/10.1017/s1755048308000412.
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AbstractThe Association of Religion Data Archives (ARDA) currently archives over 500 local, national, and international data files, and offers a wide range of research tools to build surveys, preview data online, develop customized maps and reports of United States church membership, and examine religion differences across nations and regions of the world. The ARDA also supports reference and teaching tools that draw on the rich data archive. This research article offers a brief introduction to the quantitative data available for exploration or download, and a few of the website features most useful for research and teaching. Supported by the Lilly Endowment, the John Templeton Foundation, the Pennsylvania State University, and the Baylor Institute for Studies of Religion, all data downloads and online services are free of charge.
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Wang, Fen-Jiao, Chang-Lin Mei, Zhi Zhang, and Qiu-Xia Xu. "Testing for Local Spatial Association Based on Geographically Weighted Interpolation of Geostatistical Data with Application to PM2.5 Concentration Analysis." Sustainability 14, no. 21 (November 7, 2022): 14646. http://dx.doi.org/10.3390/su142114646.
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Using local spatial statistics to explore local spatial association of geo-referenced data has attracted much attention. As is known, a local statistic is formulated at a particular sampling unit based on a prespecific proximity relationship and the observations in the neighborhood of this sampling unit. However, geostatistical data such as meteorological data and air pollution data are generally collected from meteorological or monitoring stations which are usually sparsely located or highly clustered over space. For such data, a local spatial statistic formulated at an isolate sampling point may be ineffective because of its distant neighbors, or the statistic is undefinable in the sub-regions where no observations are available, which limits the comprehensive exploration of local spatial association over the whole studied region. In order to overcome the predicament, a local-linear geographically weighted interpolation method is proposed in this paper to obtain the predictors of the underlying spatial process on a lattice spatial tessellation, on which a local spatial statistic can be well formulated at each interpolation point. Furthermore, the bootstrap test is suggested to identify the locations where local spatial association is significant using the interpolated-value-based local spatial statistics. Simulation with comparison to some existing interpolation and test methods is conducted to assess the performance of the proposed interpolation and the suggested test methods and a case study based on PM2.5 concentration data in Guangdong province, China, is used to demonstrate their applicability. The results show that the proposed interpolation method performs accurately in retrieving an underlying spatial process and the bootstrap test with the interpolated-value-based local statistics is powerful in identifying local patterns of spatial association.
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Xiao, Mengli, Zhong Zhuang, and Wei Pan. "Local Epigenomic Data are more Informative than Local Genome Sequence Data in Predicting Enhancer-Promoter Interactions Using Neural Networks." Genes 11, no. 1 (December 29, 2019): 41. http://dx.doi.org/10.3390/genes11010041.
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Enhancer-promoter interactions (EPIs) are crucial for transcriptional regulation. Mapping such interactions proves useful for understanding disease regulations and discovering risk genes in genome-wide association studies. Some previous studies showed that machine learning methods, as computational alternatives to costly experimental approaches, performed well in predicting EPIs from local sequence and/or local epigenomic data. In particular, deep learning methods were demonstrated to outperform traditional machine learning methods, and using DNA sequence data alone could perform either better than or almost as well as only utilizing epigenomic data. However, most, if not all, of these previous studies were based on randomly splitting enhancer-promoter pairs as training, tuning, and test data, which has recently been pointed out to be problematic; due to multiple and duplicating/overlapping enhancers (and promoters) in enhancer-promoter pairs in EPI data, such random splitting does not lead to independent training, tuning, and test data, thus resulting in model over-fitting and over-estimating predictive performance. Here, after correcting this design issue, we extensively studied the performance of various deep learning models with local sequence and epigenomic data around enhancer-promoter pairs. Our results confirmed much lower performance using either sequence or epigenomic data alone, or both, than reported previously. We also demonstrated that local epigenomic features were more informative than local sequence data. Our results were based on an extensive exploration of many convolutional neural network (CNN) and feed-forward neural network (FNN) structures, and of gradient boosting as a representative of traditional machine learning.
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Tao, Feng, Rengan Suresh, Johnathan Votion, and Yongcan Cao. "Graph Based Multi-Layer K-Means++ (G-MLKM) for Sensory Pattern Analysis in Constrained Spaces." Sensors 21, no. 6 (March 16, 2021): 2069. http://dx.doi.org/10.3390/s21062069.
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In this paper, we focus on developing a novel unsupervised machine learning algorithm, named graph based multi-layer k-means++ (G-MLKM), to solve the data-target association problem when targets move on a constrained space and minimal information of the targets can be obtained by sensors. Instead of employing the traditional data-target association methods that are based on statistical probabilities, the G-MLKM solves the problem via data clustering. We first develop the multi-layer k-means++ (MLKM) method for data-target association at a local space given a simplified constrained space situation. Then a p-dual graph is proposed to represent the general constrained space when local spaces are interconnected. Based on the p-dual graph and graph theory, we then generalize MLKM to G-MLKM by first understanding local data-target association, extracting cross-local data-target association mathematically, and then analyzing the data association at intersections of that space. To exclude potential data-target association errors that disobey physical rules, we also develop error correction mechanisms to further improve the accuracy. Numerous simulation examples are conducted to demonstrate the performance of G-MLKM, which yields an average data-target association accuracy of 92.2%.
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Zhang, Weijie, Jun Zhao, Wenkai Liu, Zhangzhi Tan, and Hanfa Xing. "Geographically Weighted Flow Cross K-Function for Network-Constrained Flow Data." Applied Sciences 12, no. 24 (December 13, 2022): 12796. http://dx.doi.org/10.3390/app122412796.
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Network-constrained spatial flows are usually used to describe movements between two spatial places on a road network. The analysis of the spatial associations between different types of network-constrained spatial flows plays a key role in understanding the spatial relationships among different movements. However, existing studies usually do not consider the effect of distance decay, which may reduce the effectiveness of the detected bivariate spatial flow patterns. Moreover, most existing studies are based on the planar space assumption, which is not suitable for network-constrained spatial flows. To overcome these problems, this study proposed a new statistical method, the Geographically Weighted Network Flow Cross K-function, which improves the Flow Cross K-Function method by taking the distance decay effect and the constraints of road networks into account. Both global and local versions are extended in this study: the global version measures the overall spatial association and the local version identifies the exact locations where a spatial association occurs. The experiments on simulated datasets show that the proposed method can identify predefined bivariate flow patterns. In a case study, the proposed method is also applied to flow data comprising Xiamen taxi and ride-hailing datasets. The results demonstrate that the proposed method effectively identifies the competitive relationships between taxi and ride-hailing services.
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Bhattacharya, Arjun, Yun Li, and Michael I. Love. "MOSTWAS: Multi-Omic Strategies for Transcriptome-Wide Association Studies." PLOS Genetics 17, no. 3 (March 8, 2021): e1009398. http://dx.doi.org/10.1371/journal.pgen.1009398.
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Traditional predictive models for transcriptome-wide association studies (TWAS) consider only single nucleotide polymorphisms (SNPs) local to genes of interest and perform parameter shrinkage with a regularization process. These approaches ignore the effect of distal-SNPs or other molecular effects underlying the SNP-gene association. Here, we outline multi-omics strategies for transcriptome imputation from germline genetics to allow more powerful testing of gene-trait associations by prioritizing distal-SNPs to the gene of interest. In one extension, we identify mediating biomarkers (CpG sites, microRNAs, and transcription factors) highly associated with gene expression and train predictive models for these mediators using their local SNPs. Imputed values for mediators are then incorporated into the final predictive model of gene expression, along with local SNPs. In the second extension, we assess distal-eQTLs (SNPs associated with genes not in a local window around it) for their mediation effect through mediating biomarkers local to these distal-eSNPs. Distal-eSNPs with large indirect mediation effects are then included in the transcriptomic prediction model with the local SNPs around the gene of interest. Using simulations and real data from ROS/MAP brain tissue and TCGA breast tumors, we show considerable gains of percent variance explained (1–2% additive increase) of gene expression and TWAS power to detect gene-trait associations. This integrative approach to transcriptome-wide imputation and association studies aids in identifying the complex interactions underlying genetic regulation within a tissue and important risk genes for various traits and disorders.
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Mohamadkhani, Mohammad, and Aydin Shishegaran. "Identifying Associations between Local Drought and Global Sea Surface Temperature." Journal of Research in Science, Engineering and Technology 8, no. 3 (September 29, 2020): 1–4. http://dx.doi.org/10.24200/jrset.vol8iss3pp1-4.
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It is clear that droughts have a fundamental impact on many different elements of society. To reduce the drought-related losses, it is necessary to give decision makers visibility into relationships of oceanic-atmospheric parameters that cause drought. The main target of this paper is to show the efficiency of data mining methods (especially association rules mining) for Identifying the associations between local droughts and large scale oceanic-atmospheric climate phenomena such as Sea Surface Temperature (SST). In this paper, association rules mining technique was offered to discover affiliation between drought of Urmia synoptic station (located in Iran) and de-trend SSTs of the Black, Mediterranean and Red Seas. To examine the accuracy of the rules, the confidence measures of the rules were calculated and compared for different considering lag times. The computed measures confirm reliable performance of the association rules mining method to monitor local drought so that the confidence between the monthly Standardized Precipitation Index (SPI) values and the de-trend SST of seas is higher than 87 percent.
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Zhu, Lilu, Xiaolu Su, Yanfeng Hu, Xianqing Tai, and Kun Fu. "A Spatio-Temporal Local Association Query Algorithm for Multi-Source Remote Sensing Big Data." Remote Sensing 13, no. 12 (June 14, 2021): 2333. http://dx.doi.org/10.3390/rs13122333.
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It is extremely important to extract valuable information and achieve efficient integration of remote sensing data. The multi-source and heterogeneous nature of remote sensing data leads to the increasing complexity of these relationships, and means that the processing mode based on data ontology cannot meet requirements any more. On the other hand, the multi-dimensional features of remote sensing data bring more difficulties in data query and analysis, especially for datasets with a lot of noise. Therefore, data quality has become the bottleneck of data value discovery, and a single batch query is not enough to support the optimal combination of global data resources. In this paper, we propose a spatio-temporal local association query algorithm for remote sensing data (STLAQ). Firstly, we design a spatio-temporal data model and a bottom-up spatio-temporal correlation network. Then, we use the method of partition-based clustering and the method of spectral clustering to measure the correlation between spatio-temporal correlation networks. Finally, we construct a spatio-temporal index to provide joint query capabilities. We carry out local association query efficiency experiments to verify the feasibility of STLAQ on multi-scale datasets. The results show that the STLAQ weakens the barriers between remote sensing data, and improves their application value effectively.
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Pothier, Yvonne M., and Christine M. Nickerson. "Our Heritage: Learning Data-Management Skills Meaningfully." Teaching Children Mathematics 4, no. 2 (October 1997): 82–88. http://dx.doi.org/10.5951/tcm.4.2.0082.
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During January, the local Heritage Association was planning and promoting various projects to celebrate Heritage Day in February. Mrs. Nickerson's fifth-grade classroom was beginning a unit on data management, to be assisted by Ms. Pothier, a university mathematics educator, for three mathematics classes a week.
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Lee and Kim. "Financial Support and University Performance in Korean Universities: A Panel Data Approach." Sustainability 11, no. 20 (October 22, 2019): 5871. http://dx.doi.org/10.3390/su11205871.
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This study analyzes the relationship between governmental financial support and university performance to determine whether the former enhances the latter or if universities enhance performance to attain government financial support. The types of financial support to universities considered in this study include those from central and local governments. University performance is defined in terms of the job-finding rates of students, number of publications in South Korean academic journals per full-time faculty member, and number of publications in SCI journals per full-time faculty member. This study uses financial support data of 148 universities from 2009 to 2017. To investigate the relationship between university financial support and performance, we use panel Granger causality testing and panel vector auto-regressive modeling. The results show that both central and local governmental financial support have an endogenous association with students’ job-finding rates. However, local governmental financial support and research performance show a reverse causality association.
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Yang, Cheng-Hong, Sin-Hua Moi, Yu-Da Lin, and Li-Yeh Chuang. "Genetic Algorithm Combined with a Local Search Method for Identifying Susceptibility Genes." Journal of Artificial Intelligence and Soft Computing Research 6, no. 3 (July 1, 2016): 203–12. http://dx.doi.org/10.1515/jaiscr-2016-0015.
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Abstract Detecting genetic association models between single nucleotide polymorphisms (SNPs) in various disease-related genes can help to understand susceptibility to disease. Statistical tools have been widely used to detect significant genetic association models, according to their related statistical values, including odds ratio (OR), chi-square test (χ2), p-value, etc. However, the high number of computations entailed in such operations may limit the capacity of such statistical tools to detect high-order genetic associations. In this study, we propose lsGA algorithm, a genetic algorithm based on local search method, to detect significant genetic association models amongst large numbers of SNP combinations. We used two disease models to simulate the large data sets considering the minor allele frequency (MAF), number of SNPs, and number of samples. The three-order epistasis models were evaluated by chi-square test (χ2) to evaluate the significance (P-value < 0.05). Analysis results showed that lsGA provided higher chi-square test values than that of GA. Simple linear regression indicated that lsGA provides a significant advantage over GA, providing the highest β values and significant p-value.
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Chu, Brian, Christopher D. Markeson, and John S. Barbieri. "Association of air pollution and chronic inflammatory skin diseases: Challenges of Google Trends data and importance of local data." Journal of the American Academy of Dermatology 83, no. 3 (September 2020): e217-e218. http://dx.doi.org/10.1016/j.jaad.2020.05.047.
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Shean, John, and Molly French. "Go Local: Innovating Local Health Departments' Engagement on Alzheimer’s." Innovation in Aging 4, Supplement_1 (December 1, 2020): 57. http://dx.doi.org/10.1093/geroni/igaa057.186.
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Abstract The aging Baby Boom generation is a major force behind projected increases in the prevalence of Alzheimer’s, which is expected to grow from 5.8 million (2020) to 13.8 million (2050). Local health departments play a major role connecting people living with dementia (and their caregivers) to services, supports, and education, and to ensure safe, accessible environments where they can flourish. From September 2019-July 2020, two local health departments (from San Diego County and the City of Boston) participated in a yearlong collaborative pilot project with the Alzheimer’s Association to advance cognitive health, dementia, and caregiving issues in their local jurisdictions. The National Association of County and City Health Officials (NACCHO) provided expert guidance and input throughout the collaboration. As part of the project, the local health departments: scanned their current work on healthy aging, identified existing data sources, and examined how existing healthy equity initiatives can apply to cognitive health, dementia, and caregiving issues. Action plans were developed, with a focus on policy mechanisms to initiate and sustain these projects and workforce development initiatives. Plans corresponded to actions of the Healthy Brain Initiative Road Map, helping elevate recommendations to change systems, policies, and environments. In fall 2020, LHDs will be able to use best practices, case studies, and tools developed from San Diego’s and Boston’s pilots to address Alzheimer’s as a chronic condition. The tools will help them engage health officials, develop action plans, and train the public health
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Kruse, R., and M. Steinbrecher. "Visual data analysis with computational intelligence methods." Bulletin of the Polish Academy of Sciences: Technical Sciences 58, no. 3 (September 1, 2010): 393–401. http://dx.doi.org/10.2478/v10175-010-0037-z.
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Visual data analysis with computational intelligence methodsVisual data analysis is an appealing and increasing field of application. We present two related visual analysis approaches that allow for the visualization of graphical model parameters and time-dependent association rules. When the graphical model is defined over purely nominal attributes, its local structure can be interpreted as an association rule. Such association rules comprise one of the most prominent and wide-spread analysis techniques for pattern detection, however, there are only few visualization methods. We introduce an alternative visual representation that also incorporates time since patterns are likely to change over time when the underlying data was collected from real-world processes. We apply the technique to both an artificial and a complex real-life dataset and show that the combined automatic and visual approach gives more and faster insight into the data than a fully-automatic approach only. Thus, our proposed method is capable of reducing considerably the analysis time.
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Ichniowski, Casey, and Jeffrey S. Zax. "Today's Associations, Tomorrow's Unions." ILR Review 43, no. 2 (January 1990): 191–208. http://dx.doi.org/10.1177/001979399004300202.
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This paper investigates the effects of association-style unionism on union membership. In a 1984 Harris poll examining workers' attitudes toward various forms of employee organization, nearly half of all nonunion workers indicated they would join an association, but most of these potential association members said they would not vote for a union to serve as a bargaining agent. Analysis of census data on local government departments strongly suggests, however, that the substitution away from traditional bargaining representation attributable to associations would be followed by an increase in the membership of traditional unions. Specifically, the authors find that in all local government services, the presence of an association in 1977 was a strong predictor of the formation of a bargaining unit by 1982—holding constant other important determinants of public employee unionism, including the legal environment.
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Zhang, Lifeng. "Systematically Exploring Associations among Multivariate Data." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6786–94. http://dx.doi.org/10.1609/aaai.v34i04.6158.
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Detecting relationships among multivariate data is often of great importance in the analysis of high-dimensional data sets, and has received growing attention for decades from both academic and industrial fields. In this study, we propose a statistical tool named the neighbor correlation coefficient (nCor), which is based on a new idea that measures the local continuity of the reordered data points to quantify the strength of the global association between variables. With sufficient sample size, the new method is able to capture a wide range of functional relationship, whether it is linear or nonlinear, bivariate or multivariate, main effect or interaction. The score of nCor roughly approximates the coefficient of determination (R2) of the data which implies the proportion of variance in one variable that is predictable from one or more other variables. On this basis, three nCor based statistics are also proposed here to further characterize the intra and inter structures of the associations from the aspects of nonlinearity, interaction effect, and variable redundancy. The mechanisms of these measures are proved in theory and demonstrated with numerical analyses.
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Ziginskiene, Edita, Vytautas Kuzminskis, Kristina Petruliene, Ruta Vaiciuniene, Asta Stankuviene, and Inga Arune Bumblyte. "Renal Anemia Control in Lithuania: Influence of Local Conditions and Local Guidelines." Scientific World Journal 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/260915.
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Erythropoietin stimulating agents had a long haul in Lithuania—we had no epoetin till 1994 and there was no intravenous iron in 2001–2004. The aim of this study was to assess the changes of renal anemia control in hemodialysis patients from early independence of Lithuania till nowadays and to evaluate the link of anemia with hospitalization rates and survival and hemoglobin variability in association with mortality. In December of each year since 1996 all hemodialysis centers have been visited and data has been collected using special questionnaires. The history of renal anemia control in Lithuania was complicated; however, a significant improvement was achieved: 54.7% of hemodialysis patients reached the target hemoglobin; all patients have a possibility of treatment with epoetin and intravenous iron. The involuntary experiment with an intravenous iron occurred in Lithuania because of economic reasons and confirmed the significant role of intravenous iron in the management of renal anemia. Hemoglobin below 100 g/L was associated with a 2.5-fold increase in relative risk of death and 1.7-fold increase in relative risk of hospitalization in Lithuanian hemodialysis patients. Although hemoglobin variability was common in Lithuanian hemodialysis patients, we did not find the association between hemoglobin variability and all-cause mortality in our study.
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Gao, Shu Tao. "A New Distributed Mining Association Rules Algorithm in Distributed Database System." Advanced Materials Research 143-144 (October 2010): 658–62. http://dx.doi.org/10.4028/www.scientific.net/amr.143-144.658.
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The traditional algorithms create the local candidate sets firstly, and then determine whether the local frequent item sets is the global frequent item sets by the traffic between the nodes. The most different between the proposed algorithm and the traditional algorithms is that it firstly generates all the local frequent item sets at each node and then communicates to the top point. At the top point, there are four cases to deal with all the local frequent item sets. For the fastest case, the determination could be made by the completion of round-trip communications. At the same time, all the operations of this algorithm are completed not by traditional data storage but by a new data storage in which the item is considered as the keyword. The method can save storage space, especially for sparse data. So the support can be calculated by the intersection of the transaction sets, which is much easier than by accessing to the database. Finally, the association rules in the distributed database are mined
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Farley, Bill. "Self-Report Accuracy in Local Economic Development Programs." Economic Development Quarterly 34, no. 4 (July 7, 2020): 315–24. http://dx.doi.org/10.1177/0891242420937800.
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Local economic development programs are primarily aimed at increasing employment and tax revenues. Data on these programs are collected through self-report surveys conducted by the International City Managers Association and others. This study evaluates predictors of accurate self-reporting. Using agency theory as a theoretical framework, the study measures the quantity of internal reporting components and the quality of financial reporting and evaluates how these are associated with accurate self-reporting. As a control, the condition of the local economy is also evaluated. The findings indicate a statistically significant relationship between the quality of financial reporting and the strength of a local economy with accurate self-reporting. Recommendations to improve research in this area are for the Government Finance Officers Association and the International City Managers Association to work together, with the former creating standards for reporting on local economic development programs and the latter aligning its survey with these standards.
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Roberts, Aki, John M. Roberts, and Raymond V. Liedka. "Elements of Terrorism Preparedness in Local Police Agencies, 2003-2007." Crime & Delinquency 58, no. 5 (September 2012): 720–47. http://dx.doi.org/10.1177/0011128712452960.
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Different elements of local police agencies’ terrorism preparedness may be associated with different organizational/environmental variables. We use 2003-2007 data (showing considerable adoption and desistance of practices) on medium-to-large-sized local agencies to examine relationships between contingency (vulnerability, organizational characteristics) and contagion (network/isomorphic influence) measures and preparedness elements, including terrorism special units, dedicated assignment of personnel, terrorism-related community outreach, computerized intelligence files, and interagency-shared radio frequencies. Modeling 2007 preparedness revealed consistencies and some differences in the associations between these measures and the different preparedness elements. The finding of no association between objective vulnerability score and any terrorism preparedness action particularly warrants further research attention. It will also be important to extend preparedness research into the recent period of economic recession.
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Cross, William P., and Scott Pruysers. "The Local Determinants of Representation: Party Constituency Associations, Candidate Nomination and Gender." Canadian Journal of Political Science 52, no. 3 (August 6, 2019): 557–74. http://dx.doi.org/10.1017/s0008423919000064.
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AbstractIt is well established that political parties play a key role as gatekeepers to elected office. This article explores the local determinants of a diverse candidate pool. In particular, we seek to uncover the district- or riding-specific party factors that are related to women's participation in the parties’ candidate nomination stages. That is, why do some nomination races in a party have no women contestants, while others have many? Using data from an original survey of party constituency association presidents, as well as extensive nomination data from Elections Canada, we demonstrate that a number of local factors are related to the presence of women contesting a party's nomination. Local party associations with a woman serving as president, as well as associations that hold earlier and longer nominations, are significantly more likely to see a woman enter the contest. The results are important since they call attention to what parties do at the grassroots level, as well as highlight practical solutions for parties seeking to have more diversity in their candidate pool.
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Zhou, Wei. "Big Data-Driven Hierarchical Local Area Network Security Risk Event Prediction Algorithm." Scientific Programming 2022 (February 8, 2022): 1–13. http://dx.doi.org/10.1155/2022/4960360.
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Big data processing technology has attracted a lot of attention due to its forecasting and warning of Internet security situation. The current risk assessment system still has problems such as high false alarm rate and excessive reliance on expert knowledge in the security defense system. Based on the big data-driven principle, this paper constructs a hierarchical local area network security risk event prediction model and proposes a predictive complex event processing method. The model building process is evolved and improved on the basis of the scoring function. The establishment method of vulnerability database and vulnerability association database is introduced in detail. At the same time, the problem of the difference between the structure and identification method of the information in the information database and the vulnerability database is solved, and the effect of timely modification when the data do not match is realized. Experimental results show that the algorithm has an accuracy of 98.75% and a fault tolerance rate of 0.0035, which promotes the accuracy of the network risk assessment results based on multistage network attacks.
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Ukwu, H. O., and S. N. Ibe. "Relationship between markers and quantitative traits in the Nigerian local chicken." Nigerian Journal of Animal Production 39, no. 1 (January 16, 2021): 3–12. http://dx.doi.org/10.51791/njap.v39i1.2247.
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A 20-week experiment was conducted to determine the relationship between markers and some quantitative traits in the Nigerian Local chicken. A total of fifty normal female chickens, about 16-18 weeks of age were used for the study. Data were collected bi-weekly on physiological and biochemical markers (packed cell volume, erythrocyte sedimentation rate, leucocyte count, blood haemoglobin, blood glucose, rectal temperature) and quantitative traits (egg weight, shell thickness, Haugh unit, body weight, short term egg production) from each bird. The association between each identified marker and the quantitative traits was determined using Pearson's product moment correlation coefficient. Rectal temperature showed significant (P < 0.05) positive association with shell thickness and body weight. Packed cell volume showed significant (p < 0.05) positive association with Haugh unit. However, significant (p < 0.01) negative association was found between rectal temperature and Haugh unit. Packed cell volume showed significant (p < 0.01) negative association with shell thickness and egg weight (p < 0.05). Other markers did not show any significant association with the quantitative traits studied. The results of this study suggest that since packed cell volume and rectal temperature showed definite association with important quantitative traits, they should be included in the marker bank that could be used by animal breeders and producers in marker assisted selection.
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Stedman, Mike, Adrian Heald, Adam Robinson, Mark Davies, and Patrick Harnett. "Associations and mitigations: an analysis of the changing risk factor landscape for chronic kidney disease in primary care using national general practice level data." BMJ Open 12, no. 12 (December 2022): e064723. http://dx.doi.org/10.1136/bmjopen-2022-064723.
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ObjectivesEarly recognition of chronic kidney disease (CKD) should be achieved by every modern healthcare system. The objective of this study was to investigate CKD risk factor trends in England using general practice level data.DesignObservational analysis of data at practice level for all general practices in England. Practice characteristics identified as potential CKD risk factors included comorbidities and local demography. Data were analysed using both univariate and multivariate analysis to identify significant factors that were associated with CKD diagnosis for the period 1 April 2019 to 31 March 2020.SettingPublicly available data from UK primary care sources including Primary Care Quality and Outcomes Framework database, practice-level prescribing data from the British National Formulary and Public Health England health outcome data.ParticipantsAll data submitted from 6471 medium to large practices in England were included (over 46 million patients).Risk factor analysisPotential risk factors were grouped into four classes based on existing literature: demographic factors, comorbidities, service and practice outcome factors, and prescribing data effects.ResultsThe original model’s prediction of CKD improved from r20.38 to an r2of 0.66 when updated factors were included. Positive associations included known risk factors with higher relative risk such as hypertension and diabetes, along with less recognised factors such as depression and use of opiates. Negative associations included NSAIDs which are traditionally associated with increased CKD risk, and prescribing of antibiotics, along with more northerly locations.ConclusionsCKD is a preventable disease with high costs and consequences. These data and novel analysis give clearer relative risk values for different patient characteristics with some unexpected findings such as potential harmful association between CKD and opiates, and a more benign association with NSAIDs. A deeper understanding of CKD risk factors is important to update and implement local and national management strategies. Further research is required to establish the causal nature of these associations and to refine location appropriate actions to minimise harm from CKD on regional and local levels.
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Ahn, YongJin, JiYoung Park, Tim A. Bruckner, and Simon Choi. "Do local employment centers modify the association between neighborhood urban form and individual obesity?" Environment and Planning A: Economy and Space 50, no. 5 (March 28, 2018): 1128–43. http://dx.doi.org/10.1177/0308518x18765478.
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Extensive literature examines the relation between land use patterns and obesity, but less work explores whether local employment centers may reduce obesity. Local employment centers may affect obesity via providing agglomeration benefits such as increased job/transportation opportunities and closer proximity to local facilities/destinations. We utilized a large serial cross-sectional health survey from Los Angeles, California, conducted over three periods, to examine whether the presence of local employment centers modifies the association between land use patterns and individual body mass index. We retrieved individual health and sociodemographic data from the Los Angeles County Health Survey (2002, 2005, and 2007). To this Health Survey, we linked land use attributes at the census tract level collected from the Southern California Association of Governments. Our log-transformed regression models present interactions between local employment centers, neighborhood urban form features, and body mass index. Although most findings are consistent with previous studies, some of land use factors hypothesized to reduce the risk of obesity could have counterintuitive associations unless local employment centers were controlled. The unexpected results of our land use coefficients indicate that the tenet of New Urbanism may not necessarily promote health benefits. Our findings suggest that modifying the built environment may be effective in reducing obesity only in areas with high degree of local employment centers. Future studies would benefit from longitudinal and experimental, rather than cross-sectional, study designs that rigorously test the potential causal role of New Urbanism on obesity.
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van Ansem, Wilke JC, Carola TM Schrijvers, Gerda Rodenburg, and Dike van de Mheen. "Is there an association between the home food environment, the local food shopping environment and children's fruit and vegetable intake? Results from the Dutch INPACT study." Public Health Nutrition 16, no. 7 (August 8, 2012): 1206–14. http://dx.doi.org/10.1017/s1368980012003461.
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AbstractObjectiveTo examine: (i) the association between home availability of fruit and vegetables and children's fruit and vegetable intake; (ii) the association between parental perception of the local food shopping environment and the home availability of fruit and vegetables; and (iii) whether the home availability of fruit and vegetables mediates the association between parental perception of the local food environment and children's fruit and vegetable consumption.DesignCross-sectional study.SettingA total of ninety-one primary schools in the Netherlands.SubjectsIn total 1501 primary caregivers completed a questionnaire to measure children's fruit and vegetable consumption, home availability of fruit and vegetables, parental perceptions of the local food shopping environment (price, quality and availability), the child's socio-economic status, the child's ethnicity and maternal height and weight.ResultsThe home availability of fruit and vegetables was positively associated with children's fruit and vegetable intake (P < 0·01 and P < 0·001, respectively). Negative parental perceptions of the local food shopping environment were associated with less fruit available at home (P < 0·05, P < 0·01 and P < 0·05 for price, quality and availability of fruit, respectively). No significant associations were found between parental perception of the local food shopping environment and children's fruit and vegetable consumption. We found no evidence that home availability of fruit and vegetables mediates the association between parental perception of the local food environment and children's fruit and vegetable intake.ConclusionsInterventions focusing on improving the home availability of fruit and vegetables may help to increase children's fruit and vegetable consumption. However, more data are required on factors influencing the home availability of fruit and vegetables.
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Lang, Konrad, Sarah Stryeck, David Bodruzic, Manfred Stepponat, Slave Trajanoski, Ursula Winkler, and Stefanie Lindstaedt. "CyVerse Austria—A Local, Collaborative Cyberinfrastructure." Mathematical and Computational Applications 25, no. 2 (June 24, 2020): 38. http://dx.doi.org/10.3390/mca25020038.
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Life sciences (LS) are advanced in research data management, since LS have established disciplinary tools for data archiving as well as metadata standards for data reuse. However, there is a lack of tools supporting the active research process in terms of data management and data analytics. This leads to tedious and demanding work to ensure that research data before and after publication are FAIR (findable, accessible, interoperable and reusable) and that analyses are reproducible. The initiative CyVerse US from the University of Arizona, US, supports all processes from data generation, management, sharing and collaboration to analytics. Within the presented project, we deployed an independent instance of CyVerse in Graz, Austria (CAT) in frame of the BioTechMed association. CAT helped to enhance and simplify collaborations between the three main universities in Graz. Presuming steps were (i) creating a distributed computational and data management architecture (iRODS-based), (ii) identifying and incorporating relevant data from researchers in LS and (iii) identifying and hosting relevant tools, including analytics software to ensure reproducible analytics using Docker technology for the researchers taking part in the initiative. This initiative supports research-related processes, including data management and analytics for LS researchers. It also holds the potential to serve other disciplines and provides potential for Austrian universities to integrate their infrastructure in the European Open Science Cloud.
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Pogodzinski, Ben, Sarah Winchell Lenhoff, and Michael Addonizio. "The Relationship Between Open Enrollment and School Bond Voting." Educational Administration Quarterly 55, no. 3 (October 29, 2018): 510–34. http://dx.doi.org/10.1177/0013161x18809343.
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Purpose: The purpose of this study was to identify an association between student mobility through open enrollment and voter support for school bond proposals. Specifically, we hypothesized that higher percentages of nonresident enrollment in a school district and resident exit from a district would be associated with lower levels of voter support for bond proposals. Data Collection and Analysis: We utilized publicly available data on bond proposals placed on ballots between 2009 and 2015, publicly available data from the State of Michigan for information on percentages of nonresident enrollment and resident exit, and publicly available data from the U.S. Census Bureau for data on district resident characteristics. Regression analysis was used to identify associations between nonresident enrollment and resident exit with the percentage of “yes” votes on school bond proposals controlling for community and resident characteristics. Findings: We failed to reject the null hypotheses, finding no statistically significant association between nonresident enrollment and resident exit and average voter support for school bond proposals, ceteris paribus. Implications for Research/Practice: We laid some groundwork for reconceptualizing the relationship between open enrollment policies and communities’ willingness to support local public schools. This has potential implications for both local- and state-level policies regarding enrollment issues and issues of school finance. As local boards continue to struggle with budget shortfalls and mounting capital needs, they may need to further weigh their own communities’ interest in supporting local public schools in the wake of increased student mobility in and out of districts.
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Hammer, Tove H., and David L. Wazeter. "Dimensions of Local Union Effectiveness." ILR Review 46, no. 2 (January 1993): 302–19. http://dx.doi.org/10.1177/001979399304600206.
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The authors develop a model of union effectiveness based on an analysis of organizational goals and use it to interpret data on 511 teachers' union locals in Pennsylvania. A factor analysis identifies five dimensions of union effectiveness in the locals: the quality or extent of (a) member participation, (b) the union's preparations for negotiations, (c) the union's involvement in political and civic activities, (d) a “union mentality” (union members' perception of the union as a political interest group representing them rather than merely an association that “meets and confers” with the school administration), and (e) the union's leadership. All of these dimensions except (b) are found to contribute significantly to overall union effectiveness; (d) and (e) are the most important components.
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Zhou, Chunlei, Xinwei Dong, Liang Ji, Bijun Zhang, Zhongping Xu, and Chengping Zhang. "Hierarchical mining algorithm for high dimensional spatiotemporal big data based on association rules." E3S Web of Conferences 256 (2021): 02040. http://dx.doi.org/10.1051/e3sconf/202125602040.
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The traditional data mining algorithm focuses too much on a single dimension of data time or space, ignoring the association between time and space, which leads to a large amount of computation and low processing efficiency of the mining algorithm and makes it difficult to guarantee the final data mining effect. In response to the above problems, a hierarchical mining algorithm based on association rules for high-dimensional spatio-temporal big data is proposed. Based on the traditional association rules, after establishing the association rules of spatio-temporal data, the data to be mined are cleaned for redundancy. After selecting the local linear embedding algorithm to reduce the dimensionality of the data, a hierarchical mining strategy is developed to realize high-dimensional spatio-temporal big data mining by searching frequent predicates to form a spatio-temporal transaction database. The simulation experiment results verify that the algorithm has high complexity and can effectively reduce the processing volume, which can improve the processing efficiency by at least 56.26% compared with other algorithms.
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BreabÄn, Marius C., Adrian Graur, Alin D. Potorac, and Doru G. BÄlan. "A NOVEL SOLUTION FOR QOS IMPLEMENTATION IN DATA NETWORKS." CBU International Conference Proceedings 5 (September 24, 2017): 1055–60. http://dx.doi.org/10.12955/cbup.v5.1070.
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Current data networks carry a multitude of data types. These include high-definition video streams and other data sensitive to network delays as well as real-time voice transmissions.Active network node equipment fulfills requests, while providing network management without affecting the data availability. Starting out from this model, a new idea is based on moving the network bandwidth control at the user’s communication interface. This paper presents a new approach to setting up QoS parameters based on local upstream traffic limitation management. This approach is quite useful in providing a certain guaranteed bandwidth for the users. So, this software ensures a specific network bandwidth according to with the rights coming up from their association with a certain ”Active Directory” group of users. The necessary active network equipment in terms of basic QoS management can be replaced by a local application for data traffic limitation, while for the involved participants the remaining bandwidth for other communications has a higher degree of availability. An efficient bandwidth control can be implemented when extracting specific AD fields and transferring pre-calculated user related parameters to a local running limiter.
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Ab Rani, Nur Izzati, Syuhaida Ismail, Zainai Mohamed, and Che Maznah Mat Isa. "Challenges for Local Contractors to Compete with Other Local and Foreign Contractors in the Malaysian Construction Industry." Environment-Behaviour Proceedings Journal 6, SI4 (July 31, 2021): 45–54. http://dx.doi.org/10.21834/ebpj.v6isi4.2900.
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Despite the benefits, globalisation and liberalisation impose challenges to local contractors. Main problem statement: The local contractors’ lack of competitive advantages provides opportunities to their competitors, limiting chances to secure local projects. This study aims to appraise local contractors’ competitiveness with the objective to assess the challenges to compete in the globalisation and liberalisation. Data from the questionnaire surveys on 60 Malaysian international contractors were analysed using the RASCH model. Three challenges assessed are: unstable economic situation, stiff local competition, and building reputation difficulties. The findings are aligned with the 2021-2025 Strategic Plan to encourage local contractors to venture overseas. Keywords: Challenges, Local contractors, Foreign contractors, Malaysian Construction Industry, Globalisation, Liberalisation eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v6iSI4.2900
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Wildeman, Christopher, Kristin Turney, and Youngmin Yi. "Paternal Incarceration and Family Functioning." ANNALS of the American Academy of Political and Social Science 665, no. 1 (April 10, 2016): 80–97. http://dx.doi.org/10.1177/0002716215625042.
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This article extends research on the association between paternal incarceration and family functioning by differentiating between families with fathers who have been incarcerated in local jails, state prisons, federal prisons, and unknown types of facilities. Data from the Fragile Families and Child Wellbeing Study (FFCW) enable this finer grained analysis. We show that there are few observable differences between families with fathers incarcerated in a local, state, or federal facility and the 53 percent of families with fathers incarcerated in an unknown facility type. We test the association between facility type and family functioning using a series of fixed effects models, showing strong associations between facility type and only two of seven family outcomes. The evidence presented here suggests that family functioning does not markedly vary by type of facility, but this finding needs to be substantiated in future research.
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Das, Manish, and Debarshi Mukherjee. "Ethnic Identity Impact on Consumers’ Ethnocentric Tendencies: The Moderating Role of Acculturation and Materialism." Management and Labour Studies 45, no. 1 (December 25, 2019): 31–53. http://dx.doi.org/10.1177/0258042x19890245.
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In the era of globalization and technological advancements, ethnic identity (EID) is creating both opportunities as well as challenges for domestic and international marketers in formulating suitable marketing and branding strategies. This study attempts to investigate the role of EID in shaping consumers’ ethnocentric tendencies (CET). By analyzing data obtained from 385 surveys completed by Indian consumers, the study assessed the association of EID dimensions and consumer ethnocentrism. The findings showed that Association with Local Culture, Preserving Local Culture, Feelings towards Local Culture and Local Interpersonal Relationship enhance consumers’ CET. Materialism strengthens the effects of association for three EID dimensions and ethnocentrism, whereas acculturation weakens the association for three dimensions of EID. This study contributes to the literature, especially in the understanding of social identity theory. Practically, the findings are useful to marketers and retailers dealing with consumers in India in formulating their cultural branding strategies.
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Smith, David Horton. "Explaining the Prevalence of Voluntary Associations among 351 Massachusetts Municipalities circa 1965: Testing a Theory." China Nonprofit Review 5, no. 1 (2013): 177–93. http://dx.doi.org/10.1163/18765149-12341259.
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Abstract Data from an extensive research project in the state of Massachusetts (USA), collected in the 1960s and never before reported, are used to test a theory of association prevalence among 351 municipalities. The dependent variable to be explained was an Association Prevalence Index (total number existing) in each municipality. The Index was derived from Massachusetts Statehouse physical records for all incorporated Nonprofit Organizations (NPOs), and showed an average of 33 associations per municipality. Using bivariate correlations, the results confirmed the theory generally. Association prevalence (raw number of associations) in a municipality was positively and significantly related to larger population size, being a county administrative center, more business telephones, greater circulation of weekly newspapers (local newspapers), more service businesses, more state government agencies, more churches, larger percentage of African-Americans, and more halls/buildings available for association gatherings (meetings, events). Contrary to the theory, the socioeconomic status of municipalities was not significantly related to association prevalence. The Statehouse Association Prevalence Index was correlated very highly (r = .92) with an independent measure of association prevalence, derived from coding the “Yellow Pages” of phone books. This result indicates the reliability and general validity of both prevalence measures.
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Kandylakis, Z., K. Karantzalos, A. Doulamis, and L. Karagiannidis. "MULTIMODAL DATA FUSION FOR EFFECTIVE SURVEILLANCE OF CRITICAL INFRASTRUCTURE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W3 (October 19, 2017): 87–93. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w3-87-2017.
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Monitoring critical infrastructures, especially those that are covering wide-zones, is of fundamental importance and priority for modern surveillance systems. The concurrent exploitation of multisensor systems, can offer additional capabilities, on day and night acquisitions and different environmental/illumination conditions. Towards this direction, we have designed a multi-sensor system based on thermal, shortwave infrared and hyperspectral video sensors. Based on advanced registration, dynamic background modelling and data association techniques, possible moving targets are detected on the thermal and shortwave infrared modalities. In order to avoid the computational intensive co-registration with the hyperspectral video streams, the detected targets are projected through a local coordinate system on the hypercube image plane. The final detected and verified targets are extracted through fusion and data association, based on temporal spectral signatures and target/background statistics. The developed multisensor system for the surveillance of critical infrastructure has been validated for monitoring wide-zones against different conditions showcasing abilities for detecting and tracking moving targets through fog and smoke.
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Yeck, William L., John M. Patton, Caryl E. Johnson, David Kragness, Harley M. Benz, Paul S. Earle, Michelle R. Guy, and Nicholas B. Ambruz. "GLASS3: A Standalone Multiscale Seismic Detection Associator." Bulletin of the Seismological Society of America 109, no. 4 (May 14, 2019): 1469–78. http://dx.doi.org/10.1785/0120180308.
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Abstract The automated global real‐time association of phase picks into seismic sources comes with unique challenges when simultaneously monitoring at local, regional, and global scales. High spatial variability in seismic station density, transitory seismic data availability, and time‐varying noise characteristics of individual stations must be considered in the design of an associator that is fast and accurate with a low false association rate. These challenges are particularly apparent at the U.S. Geological Survey National Earthquake Information Center (NEIC), which monitors seismicity in near‐real time on local, regional, and global scales using seismic data from roughly 2100 real‐time seismic stations. To fully leverage this large dataset, NEIC developed a standalone self‐configuring seismic phase associator, GLobal ASSociator 3 (GLASS3) that simultaneously processes variably scaled 3D association webs, each with a unique set of nucleation criteria (e.g., nucleation stack threshold). GLASS3 has many useful features for real‐time monitoring including its computational efficiency, instantaneous pick processing, and on‐the‐fly configurability such as the creation and removal of targeted association webs and updates to supporting station metadata. GLASS3 runs both as part of a real‐time event processing system and as a configurable standalone associator that can be applied to a large variety of seismic problems. Here, we describe the GLASS3 algorithm and demonstrate (including input data and configuration files) its use in associating phase‐ambiguous picks on multiple scales.
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Aghdam, Atae Rezaei, Mostafa Kamalpour, and Alex Tze Hiang Sim. "Knowledge Discovery for Tourism Using Data Mining and Qualitative Analysis." International Journal of Asian Business and Information Management 5, no. 4 (October 2014): 48–59. http://dx.doi.org/10.4018/ijabim.2014100105.
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This paper aims to propose a new guideline for analyzing tourist profiles as found in www.tripadvisor.com. These have been examined from two different aspects so as to gain conclusive results. Tourist data were “crawled” from tripadvisor.com through a specific web crawler. Mining techniques using a combination of visualization, clustering, and association rules were instrumental in discovering the first set of interesting knowledge. This was followed by a qualitative analysis applied through Nvivo software via coding of the tourist's comments in order to define the design of the prospective model. A final set of results was obtained once both results confirmed each other. In this study, results show that there are several types of tourists; with each group having different preferences. For example: male Singaporean visitors to hotels tend to enjoy wine and food in addition to outdoor activities; while local visitors to Legoland are not satisfied with certain aspects, such as the price of food. International tourists, however, consider the affirmative points of Legoland. This research can be very useful for tourist associations and hotel managers in Johor Bahru.
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Nishihara, T., and K. Yamamura. "Local Manufacture of MMC Using FSW." Materials Science Forum 539-543 (March 2007): 3733–38. http://dx.doi.org/10.4028/www.scientific.net/msf.539-543.3733.
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Friction stir welding (FSW) has been generating interest in association with friction stir processing (FSP), a new technique that employs FSW tooling. FSP is being investigated as a thermo-mechanical processing tool to transform a heterogeneous microstructure into a more homogenous microstructure.However, very little data is available on the use of FSW for processing composite materials. In this study, a novel method of local manufacture of metal matrix composites (MMCs) using FSW is proposed and its application to friction stir spot welding (FSSW) is described. Trials investigating local manufacture of aluminum oxide particulate reinforced 6063 Al by friction stirring were carried out on a modified milling machine. The results are discussed in terms of weldability and residual microstructure.